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市場調查報告書

商品編碼

1735879

全球臨床決策支援系統 (CDSS) 市場，2024-2030年

Clinical Decision Support System Market, Global, 2024-2030

出版日期: 2025年05月09日 | 出版商:

Frost & Sullivan | 英文 54 Pages | 商品交期: 最快1-2個工作天內

價格

簡介目錄

人工智慧整合可改善臨床結果，推動轉型成長

對有效人口健康管理的日益關注，促使醫療保健機構採用下一代臨床決策支援工具，推動市場成長。醫療保健系統在臨床品質和效率方面持續面臨重大挑戰，這導致人們更加重視採用臨床決策支援系統（CDSS）。這些工具有助於在醫院和居家醫療環境中進行早期診斷和及時、有針對性的臨床干涉。它們還有助於預防患者併發症，減少住院和ICU入院等昂貴干涉措施的需求。人工智慧（AI）和機器學習（包括互動式人工智慧）的技術進步，推動 CDSS 解決方案的持續創新。

Frost & Sullivan 報告概述了全球 CDSS 市場，並對決策證據/通訊協定、決策工作流程、決策分析和決策交付等應用領域進行了詳細分析，並提供了收益預測。報告還檢驗了該市場的促進因素和限制因素，並指出了該領域變化帶來的機會，市場參與者和相關人員應該抓住這些機會。基準年為2024年，預測期間為2025-2030年。

收益預測

2024年基準年預計收益為 107.528億美元，2024年至2030年研究期間的年複合成長率為 7.6%。

主要競爭對手

Optum
EBSCO
Elsevier
Hearst Health
Merative
Medicomp Systems
Wolters Kluwer
RethinkFirst
Glass Health
UNORK
Premier Inc.（STANTON HEALTH）
Getinge
Motive Medical Intelligence
athenahealth
EvidenceCare
HCA Healthcare
MEDITECH
eClinicalWorks
Wolters Kluwer
RIMIDI
Inovalon
Vizio
Flatiron Health（Roche）
Medecision
MCG Health
Epic
Medical Informatics Corp.
Medtronic
Oracle Health
Philips Healthcare
GE Healthcare
Stat Pearls

CDSS的演變
主要用例
主要市場趨勢
主要挑戰和價值提案
消費者之聲：將人工智慧融入 CDSS
CDSS 中潛在的GenAI 用例
人工智慧驅動的供應商價值提案
監管情境：FDA 對 CDSS 的處理方法
成長指標
成長促進因素
成長抑制因素
預測相關考察
收益預測
依應用分類的收益預測
收益預測分析
價格趨勢及預測分析
各地區收益預測
CDSS解決方案吸引力分析
當地吸引力的排名和映射
各地區收益預測分析
收益佔有率：競爭熱圖
收益佔有率：競爭熱圖分析
公司聚焦

成長引擎：決策證據/通訊協定

成長指標
收益預測
各地區收益預測
預測分析

成長引擎：決策分析

成長指標
收益預測
各地區收益預測
預測分析

成長引擎：決策工作流程

成長指標
收益預測
各地區收益預測
預測分析

成長動力：決策交付

成長指標
收益預測
各地區收益預測
預測分析

成長機會宇宙

成長機會1：CDSS 中的AI
成長機會2：重症患者的即時資料
成長機會3：居家照護的照護現場CDSS

附錄與後續步驟

成長機會的益處和影響
後續步驟
附件列表
免責聲明

簡介目錄

Product Code: KB09-48

AI Integration is Driving Transformational Growth by Enabling Improvements in Clinical Outcomes

The increasing focus on effective population health management is prompting healthcare organizations to adopt next-generation clinical decision support tools that drive market growth. Healthcare systems continue to face significant clinical quality and efficiency challenges, leading to a heightened focus on implementing clinical decision support systems (CDSS). These tools facilitate early diagnosis and timely, precise clinical interventions in both hospital and home-based healthcare settings. They also help prevent complications in patient conditions, thereby reducing the need for costly interventions such as hospital readmissions and ICU admissions. Technological advancements in artificial intelligence (AI) and machine learning, including generative AI and conversational AI, are boosting ongoing innovation in CDSS solutions.

This Frost & Sullivan report provides an overview of the global CDSS market, offering a detailed analysis, including a revenue forecast, for each application segment, namely, decision evidence/protocols, decision workflow, decision analytics, and decision delivery. The report also examines the factors driving and restraining this market and identifies the opportunities emerging from the changes in this space for market players and stakeholders to leverage. The base year is 2024, and the forecast period is from 2025 to 2030.

Revenue Forecast

The revenue estimate for the base year 2024 is $10,752.8 million, with a CAGR of 7.6% for the study period from 2024 to 2030.

Scope of Analysis

Clinical decision support (CDS) provides clinicians and healthcare staff with knowledge and person-specific information that helps them improve clinical decisions and enhance patient healthcare.
A clinical decision support system (CDSS) is a broad concept with many definitions that are used variably. It encompasses a variety of tools to enhance decision-making in the clinical workflow.
CDSS includes a mix of evidence (content), analytics, workflow, devices, and software-based solutions that consist of the electronic health record (EHR) and are maintained by an IT platform.
This report delivers a detailed analysis of the CDSS market and its applications, specifically, decision evidence/protocols, decision workflow, decision analytics, and decision delivery.
The report analyzes industry challenges, drivers, and restraints, and offers a revenue forecast for each application area.
It covers important business models, the regulatory outlook, cost structures, and the competitive landscape.
Description of the top growth opportunities for the global CDSS market in the context of user relevance and calls to action has also been provided.
The revenue estimates in this study focus only on revenue attributed to CDSS. In some cases, such as analytics, electronic health records, and device companies, CDSS revenue represents a small part of a larger revenue stream.

The Impact of the Top 3 Strategic Imperatives on the CDSS Industry

Disruptive Technologies

WHY: The CDSS has witnessed significant advancements with the development and integration of new technologies such as AI, cloud, predictive analytics, and mobile platforms, and it will continue to impact CDSS workflows in the next few years. To achieve a highly accessible, flexible, and scalable CDSS solution, end users will continue to look for technology advancements.

FROST PERSPECTIVE: Companies need to identify new use cases and build a strong foundation of evidence-based content. The integration of dynamic AI, specifically, a combination of conversational AI and generative AI (GenAI), can empower end users with easy access to relevant information, enabling them to, for instance, create documents for administrative purposes.

Innovative Business Models

WHY: A high upfront installation and implementation cost has restrained the widespread adoption of CDSS solutions. CDSS has significant potential to improve healthcare outcomes with better clinical recommendations, ultimately benefiting patients and providers in terms of cost and resource utilization.

FROST PERSPECTIVE: Evolving business models such as software-as-a-service (SaaS), subscription models, and risk-based incentives created by technology vendors can provide flexibility in upfront investment and boost CDSS adoption. Growing awareness about the long-term benefits of improved health outcomes and economic growth will drive CDSS growth in the next few years.

Transformative Megatrends

WHY: Medical errors and staff burnout affect healthcare systems' ability to provide optimal patient care. Transitions to home care, a focus on value-based care, an increasing number of data sources, revisions of guidelines, and revenue losses also present significant challenges. Moreover, growing healthcare consumerism and a shift towards personalized care exhaust stakeholders in the face of critical decision-making moments. This is where CDSS has the biggest impact.

FROST PERSPECTIVE: This evolving market demands that vendors regularly update their products and features. Expanding offerings is critical to remaining a viable player. However, such developments cannot happen in isolation. Vendors need to include key end users and decision-makers in their research and development (R&D) programs to best target their investments toward those stakeholders' pain points. To stay ahead of the competition, companies must utilize both organic and inorganic growth pathways.

Key Competitors

Optum
EBSCO
Elsevier
Hearst Health
Merative
Medicomp Systems
Wolters Kluwer
RethinkFirst
Glass Health
UNORK
Premier Inc. (STANTON HEALTH)
Getinge
Motive Medical Intelligence
athenahealth
EvidenceCare
HCA Healthcare
MEDITECH
eClinicalWorks
Wolters Kluwer
RIMIDI
Inovalon
Vizio
Flatiron Health (Roche)
Medecision
MCG Health
Epic
Medical Informatics Corp.
Medtronic
Oracle Health
Philips Healthcare
GE Healthcare
Stat Pearls

Competitive Environment

Number of Competitors

>50 with revenue greater than $1.0 million

Competitive Factors

Cost, performance, support, technology, reliability, contractor relationships

Key End-user Industry Verticals

Providers, hospitals, primary care centers, medical devices, payers

Leading Competitors

Wolters Kluwer, Philips Healthcare, Optum, Hearst Health, Oracle Health

Revenue Share of Top 4 Competitors (2024)

18.3%

Other Notable Competitors

athenahealth, Elsevier, EBSCO, eClinicalWorks, Epic

Distribution Structure

OEMs, retail sales, direct sales, Cloud-based SaaS

Notable Acquisitions and Mergers

Health Catalyst acquired ARMUS Corporation; Oracle acquired Cerner

Growth Drivers

Value-based Care and Population Health Management: The shift towards value-based care models and population health management strategies has placed a greater emphasis on CDSS. These solutions can assist healthcare providers in identifying high-risk patients, stratifying populations, and developing targeted interventions. By supporting evidence-based decision-making, CDSS contribute to improved patient outcomes and better management of chronic conditions, aligning with the goals of value-based care.

Growing Demand for Personalized Medicine: Personalized medicine, which involves tailoring medical treatment to individual patients based on their unique characteristics, is gaining traction. CDSS can play a crucial role in facilitating personalized medicine by integrating patient-specific data, genetic information, and clinical guidelines to provide tailored recommendations. This growing demand for personalized medicine is a significant driver.

Rising Healthcare Costs and Resource Constraints: Healthcare systems worldwide are facing increasing financial pressures and resource constraints. CDSS can help optimize resource utilization by providing real-time clinical insights, reducing unnecessary tests and procedures, and improving overall efficiency. This cost-effectiveness aspect is a significant driver for the adoption of CDSS solutions.

Growth Restraints

Cost and Budgetary Constraints: Implementing and maintaining CDSS software can be costly, especially for smaller healthcare organizations or those with limited budgets. The investments in hardware, software licenses, infrastructure upgrades, and ongoing maintenance and support costs can be significant. Budgetary constraints may deter healthcare providers from adopting CDSS, especially if they perceive the benefits as uncertain or difficult to quantify.

Clinician Acceptance and Alert Fatigue: Clinicians may be skeptical of automated systems' accuracy or be concerned about a loss of autonomy. Moreover, too many or unimportant alerts may lead to alert fatigue among physicians, affecting the usage of CDSS.

System Integration Complexities: Variations in standards for healthcare records can present challenges in effective CDSS integration with existing hospital IT systems.